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Then, all the models were refitted using a first-order continuous-time autoregressive error structure.
New parameter estimates were acquired and the models were refitted and root mean square error (RMSE) and bias were calculated.
The final EMG-force relationship models were refitted for each of the three trials, and the participant-specific regression lines were extracted from the refitted models and compared between trials per percentile across the contraction intensity range.
Therefore, for each cytokine, the models were refitted with bootstrapping used to estimate the standard errors.
The final models were refitted to participants with complete data on the retained predictor variables.
When outliers were identified in residual plots, the models were refitted with these observations removed to determine their effects on parameter estimation.
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These models were refit to adjust for gender and education.
When taxonomic random effects were non-significant, models were refit using generalized least squares.
In this strategy, sequential sampling points are generated over the design space and Kriging models are refitted in an iterative fashion.
The models are refitted with "city" as an added control covariate.
In this test, the models are refitted and cross-validated multiple times, after permuting class labels or dependent variable values.
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